DESIGNING A RECOMMENDATION ENGINE FOR AN SFA SOFTWARE SUITE Next Case Study

Client Organization:

Mobile-app Development Company.

Project Owner:

VP, Operations & Strategy

The Problem:

A retail product distributor sends out salespersons in their delivery van equipped with mobile SFA application developed by our client to deliver products on periodic basis to the respective outlets. The salespersons were supposed to recommend the right products to the store, based on their intuition and certain other parameters such as history of the products purchased by the outlet, must sell SKUs, current inventory check, promotional schemes etc.The storeowner may or may not accept the salesperson's recommendations and sometimes the salesperson may not have enough stock in his van to meet the storeowner's demand at the time of delivery. Our client wanted us to develop a recommendation engine so that the sales utilization was optimal.

The Solution:

We feature engineered the attributes provided in the data, identified similar stores & developed a platform-independent pluggable recommendation engine which may be called from the client’s SFA software and will be able to predict/recommend the right good(s) & it quantity which may be required by a particular outlet with 92% accuracy at an average.

Tools & Technologies:

R and Java